Fix incomplete json output in guideline evaluator

[moria97]

Description

For guidelines evaluator, the code expect json output from LLM and raise exception when fail to parse json.

However, sometimes the LLM response is longer than max token due to a long feedback, the output json will be incomplete and thus break the evaluation process. This is an unintended behavior for evaluation process.

Considering we don't need very long feedbacks in evaluation, I added a 'concise hint' to the output format prompt to fix this issue.

Fixes # (issue)

New Package?

Did I fill in the tool.llamahub section in the pyproject.toml and provide a detailed README.md for my new integration or package?

• Yes
• No

Version Bump?

Did I bump the version in the pyproject.toml file of the package I am updating? (Except for the llama-index-core package)

• Yes
• No

Type of Change

Please delete options that are not relevant.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration

• Added new unit/integration tests
• Added new notebook (that tests end-to-end)
• I stared at the code and made sure it makes sense

Suggested Checklist:

• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added Google Colab support for the newly added notebooks.
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• I ran make format; make lint to appease the lint gods

[logan-markewich]

Why do we modify prompt here? There is already a very similar prompt here

llama_index/llama-index-core/llama_index/core/output_parsers/pydantic.py

Line 10 in 3445b02

PYDANTIC_FORMAT_TMPL = """

Feels like either the default prompt could be modified, or this is specific to the LLM you are using and you should just pass in a customized output parser as kwarg

[moria97]

Yes. Actually I'm overwriting the template for evaluations only because I'm not quite sure whether it's a common requirements for json output to modify the default template.
Now I feel adding a custom output parser to the constructor here makes more sense since it allows flexibility with different LLMs/settings and backward compatibility. I have added a custom output parser para now.